Overview

Brought to you by YData

Dataset statistics

Number of variables12
Number of observations2968
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory301.4 KiB
Average record size in memory104.0 B

Variable types

Numeric12

Alerts

avg_basket_size is highly overall correlated with gross_revenue and 1 other fieldsHigh correlation
avg_recency_days is highly overall correlated with frequencyHigh correlation
avg_ticket is highly overall correlated with avg_unique_basket_sizeHigh correlation
avg_unique_basket_size is highly overall correlated with avg_ticket and 1 other fieldsHigh correlation
frequency is highly overall correlated with avg_recency_daysHigh correlation
gross_revenue is highly overall correlated with avg_basket_size and 3 other fieldsHigh correlation
qtde_invoices is highly overall correlated with gross_revenue and 3 other fieldsHigh correlation
qtde_items is highly overall correlated with avg_basket_size and 3 other fieldsHigh correlation
qtde_products is highly overall correlated with avg_unique_basket_size and 3 other fieldsHigh correlation
recency_days is highly overall correlated with qtde_invoicesHigh correlation
avg_ticket is highly skewed (γ1 = 25.1569664) Skewed
frequency is highly skewed (γ1 = 24.87687084) Skewed
qtde_returns is highly skewed (γ1 = 21.9754032) Skewed
customer_id has unique values Unique
recency_days has 33 (1.1%) zeros Zeros
qtde_returns has 1481 (49.9%) zeros Zeros

Reproduction

Analysis started2025-07-15 04:03:39.454192
Analysis finished2025-07-15 04:03:53.492503
Duration14.04 seconds
Software versionydata-profiling vv4.16.1
Download configurationconfig.json

Variables

customer_id
Real number (ℝ)

Unique 

Distinct2968
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean15270.377
Minimum12347
Maximum18287
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size46.4 KiB
2025-07-15T01:03:53.540367image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Quantile statistics

Minimum12347
5-th percentile12619.35
Q113798.75
median15220.5
Q316768.5
95-th percentile17964.65
Maximum18287
Range5940
Interquartile range (IQR)2969.75

Descriptive statistics

Standard deviation1719.1445
Coefficient of variation (CV)0.11258036
Kurtosis-1.2061782
Mean15270.377
Median Absolute Deviation (MAD)1489
Skewness0.032193711
Sum45322479
Variance2955457.9
MonotonicityNot monotonic
2025-07-15T01:03:53.660825image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
12558 1
 
< 0.1%
17850 1
 
< 0.1%
13047 1
 
< 0.1%
12583 1
 
< 0.1%
13748 1
 
< 0.1%
15100 1
 
< 0.1%
15291 1
 
< 0.1%
14688 1
 
< 0.1%
16956 1
 
< 0.1%
17010 1
 
< 0.1%
Other values (2958) 2958
99.7%
ValueCountFrequency (%)
12347 1
< 0.1%
12348 1
< 0.1%
12352 1
< 0.1%
12356 1
< 0.1%
12358 1
< 0.1%
12359 1
< 0.1%
12360 1
< 0.1%
12362 1
< 0.1%
12364 1
< 0.1%
12370 1
< 0.1%
ValueCountFrequency (%)
18287 1
< 0.1%
18283 1
< 0.1%
18282 1
< 0.1%
18277 1
< 0.1%
18276 1
< 0.1%
18274 1
< 0.1%
18273 1
< 0.1%
18272 1
< 0.1%
18270 1
< 0.1%
18269 1
< 0.1%

gross_revenue
Real number (ℝ)

High correlation 

Distinct2953
Distinct (%)99.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2693.4851
Minimum6.2
Maximum279138.02
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size46.4 KiB
2025-07-15T01:03:53.768544image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Quantile statistics

Minimum6.2
5-th percentile229.7325
Q1570.845
median1085.51
Q32306.905
95-th percentile7169.562
Maximum279138.02
Range279131.82
Interquartile range (IQR)1736.06

Descriptive statistics

Standard deviation10135.465
Coefficient of variation (CV)3.7629558
Kurtosis397.30132
Mean2693.4851
Median Absolute Deviation (MAD)670.84
Skewness17.635372
Sum7994263.7
Variance1.0272766 × 108
MonotonicityNot monotonic
2025-07-15T01:03:53.871356image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
533.33 2
 
0.1%
734.94 2
 
0.1%
178.96 2
 
0.1%
1078.96 2
 
0.1%
598.2 2
 
0.1%
1314.45 2
 
0.1%
379.65 2
 
0.1%
2053.02 2
 
0.1%
331 2
 
0.1%
889.93 2
 
0.1%
Other values (2943) 2948
99.3%
ValueCountFrequency (%)
6.2 1
< 0.1%
13.3 1
< 0.1%
15 1
< 0.1%
36.56 1
< 0.1%
45 1
< 0.1%
52 1
< 0.1%
52.2 1
< 0.1%
52.2 1
< 0.1%
62.43 1
< 0.1%
68.84 1
< 0.1%
ValueCountFrequency (%)
279138.02 1
< 0.1%
259657.3 1
< 0.1%
194550.79 1
< 0.1%
140450.72 1
< 0.1%
124564.53 1
< 0.1%
117379.63 1
< 0.1%
91062.38 1
< 0.1%
72882.09 1
< 0.1%
66653.56 1
< 0.1%
65039.62 1
< 0.1%

recency_days
Real number (ℝ)

High correlation  Zeros 

Distinct272
Distinct (%)9.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean64.309299
Minimum0
Maximum373
Zeros33
Zeros (%)1.1%
Negative0
Negative (%)0.0%
Memory size46.4 KiB
2025-07-15T01:03:53.974870image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile2
Q111
median31
Q381
95-th percentile242
Maximum373
Range373
Interquartile range (IQR)70

Descriptive statistics

Standard deviation77.760922
Coefficient of variation (CV)1.2091707
Kurtosis2.7765172
Mean64.309299
Median Absolute Deviation (MAD)26
Skewness1.7980529
Sum190870
Variance6046.7611
MonotonicityNot monotonic
2025-07-15T01:03:54.083308image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 99
 
3.3%
4 87
 
2.9%
3 85
 
2.9%
2 85
 
2.9%
8 76
 
2.6%
10 67
 
2.3%
9 66
 
2.2%
7 66
 
2.2%
17 64
 
2.2%
16 55
 
1.9%
Other values (262) 2218
74.7%
ValueCountFrequency (%)
0 33
 
1.1%
1 99
3.3%
2 85
2.9%
3 85
2.9%
4 87
2.9%
5 43
1.4%
7 66
2.2%
8 76
2.6%
9 66
2.2%
10 67
2.3%
ValueCountFrequency (%)
373 2
0.1%
372 4
0.1%
371 1
 
< 0.1%
368 1
 
< 0.1%
366 4
0.1%
365 2
0.1%
364 1
 
< 0.1%
360 1
 
< 0.1%
359 1
 
< 0.1%
358 4
0.1%

qtde_invoices
Real number (ℝ)

High correlation 

Distinct56
Distinct (%)1.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5.7243935
Minimum1
Maximum206
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size46.4 KiB
2025-07-15T01:03:54.188751image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median4
Q36
95-th percentile17
Maximum206
Range205
Interquartile range (IQR)4

Descriptive statistics

Standard deviation8.8577599
Coefficient of variation (CV)1.5473709
Kurtosis190.78624
Mean5.7243935
Median Absolute Deviation (MAD)2
Skewness10.765555
Sum16990
Variance78.45991
MonotonicityNot monotonic
2025-07-15T01:03:54.284419image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2 784
26.4%
3 499
16.8%
4 393
13.2%
5 237
 
8.0%
1 190
 
6.4%
6 173
 
5.8%
7 138
 
4.6%
8 98
 
3.3%
9 69
 
2.3%
10 55
 
1.9%
Other values (46) 332
11.2%
ValueCountFrequency (%)
1 190
 
6.4%
2 784
26.4%
3 499
16.8%
4 393
13.2%
5 237
 
8.0%
6 173
 
5.8%
7 138
 
4.6%
8 98
 
3.3%
9 69
 
2.3%
10 55
 
1.9%
ValueCountFrequency (%)
206 1
< 0.1%
199 1
< 0.1%
124 1
< 0.1%
97 1
< 0.1%
91 2
0.1%
86 1
< 0.1%
72 1
< 0.1%
62 2
0.1%
60 1
< 0.1%
57 1
< 0.1%

qtde_items
Real number (ℝ)

High correlation 

Distinct1670
Distinct (%)56.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1582.1044
Minimum1
Maximum196844
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size46.4 KiB
2025-07-15T01:03:54.384590image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile102.35
Q1296
median640
Q31399.5
95-th percentile4403.25
Maximum196844
Range196843
Interquartile range (IQR)1103.5

Descriptive statistics

Standard deviation5705.2914
Coefficient of variation (CV)3.6061408
Kurtosis516.7418
Mean1582.1044
Median Absolute Deviation (MAD)421
Skewness18.737654
Sum4695686
Variance32550350
MonotonicityNot monotonic
2025-07-15T01:03:54.504269image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
310 11
 
0.4%
88 9
 
0.3%
150 9
 
0.3%
84 8
 
0.3%
260 8
 
0.3%
246 8
 
0.3%
288 8
 
0.3%
272 8
 
0.3%
1200 7
 
0.2%
114 7
 
0.2%
Other values (1660) 2885
97.2%
ValueCountFrequency (%)
1 1
< 0.1%
2 2
0.1%
12 2
0.1%
16 1
< 0.1%
17 1
< 0.1%
18 1
< 0.1%
19 1
< 0.1%
20 1
< 0.1%
23 1
< 0.1%
25 1
< 0.1%
ValueCountFrequency (%)
196844 1
< 0.1%
80263 1
< 0.1%
77373 1
< 0.1%
69993 1
< 0.1%
64549 1
< 0.1%
64124 1
< 0.1%
63312 1
< 0.1%
58343 1
< 0.1%
57885 1
< 0.1%
50255 1
< 0.1%

qtde_products
Real number (ℝ)

High correlation 

Distinct468
Distinct (%)15.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean122.76449
Minimum1
Maximum7838
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size46.4 KiB
2025-07-15T01:03:54.617966image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile9
Q129
median67
Q3135
95-th percentile382
Maximum7838
Range7837
Interquartile range (IQR)106

Descriptive statistics

Standard deviation269.93294
Coefficient of variation (CV)2.1987868
Kurtosis354.77884
Mean122.76449
Median Absolute Deviation (MAD)44
Skewness15.706135
Sum364365
Variance72863.79
MonotonicityNot monotonic
2025-07-15T01:03:54.728574image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
28 43
 
1.4%
20 37
 
1.2%
29 35
 
1.2%
35 35
 
1.2%
19 34
 
1.1%
15 33
 
1.1%
11 32
 
1.1%
26 31
 
1.0%
27 30
 
1.0%
25 30
 
1.0%
Other values (458) 2628
88.5%
ValueCountFrequency (%)
1 6
 
0.2%
2 14
0.5%
3 15
0.5%
4 17
0.6%
5 26
0.9%
6 29
1.0%
7 18
0.6%
8 19
0.6%
9 26
0.9%
10 28
0.9%
ValueCountFrequency (%)
7838 1
< 0.1%
5673 1
< 0.1%
5095 1
< 0.1%
4580 1
< 0.1%
2698 1
< 0.1%
2379 1
< 0.1%
2060 1
< 0.1%
1818 1
< 0.1%
1673 1
< 0.1%
1637 1
< 0.1%

avg_ticket
Real number (ℝ)

High correlation  Skewed 

Distinct2965
Distinct (%)99.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean32.994257
Minimum2.1505882
Maximum4453.43
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size46.4 KiB
2025-07-15T01:03:54.836521image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Quantile statistics

Minimum2.1505882
5-th percentile4.915888
Q113.118111
median17.953447
Q324.981794
95-th percentile90.052125
Maximum4453.43
Range4451.2794
Interquartile range (IQR)11.863683

Descriptive statistics

Standard deviation119.53207
Coefficient of variation (CV)3.6228143
Kurtosis812.96474
Mean32.994257
Median Absolute Deviation (MAD)5.9790186
Skewness25.156966
Sum97926.954
Variance14287.915
MonotonicityNot monotonic
2025-07-15T01:03:54.936610image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
14.47833333 2
 
0.1%
15 2
 
0.1%
4.162 2
 
0.1%
18.90403509 1
 
< 0.1%
28.9025 1
 
< 0.1%
33.86607143 1
 
< 0.1%
292 1
 
< 0.1%
45.32647059 1
 
< 0.1%
80.13043478 1
 
< 0.1%
14.43642857 1
 
< 0.1%
Other values (2955) 2955
99.6%
ValueCountFrequency (%)
2.150588235 1
< 0.1%
2.4325 1
< 0.1%
2.462371134 1
< 0.1%
2.511241379 1
< 0.1%
2.515333333 1
< 0.1%
2.65 1
< 0.1%
2.656931818 1
< 0.1%
2.707598253 1
< 0.1%
2.760621572 1
< 0.1%
2.770464191 1
< 0.1%
ValueCountFrequency (%)
4453.43 1
< 0.1%
3202.92 1
< 0.1%
1687.2 1
< 0.1%
952.9875 1
< 0.1%
872.13 1
< 0.1%
841.0214493 1
< 0.1%
651.1683333 1
< 0.1%
640 1
< 0.1%
624.4 1
< 0.1%
615.75 1
< 0.1%

avg_recency_days
Real number (ℝ)

High correlation 

Distinct1258
Distinct (%)42.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean67.302133
Minimum1
Maximum366
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size46.4 KiB
2025-07-15T01:03:55.032821image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile8
Q125.917308
median48.267857
Q385.333333
95-th percentile200.65
Maximum366
Range365
Interquartile range (IQR)59.416026

Descriptive statistics

Standard deviation63.505358
Coefficient of variation (CV)0.94358612
Kurtosis4.9080488
Mean67.302133
Median Absolute Deviation (MAD)26.267857
Skewness2.066084
Sum199752.73
Variance4032.9306
MonotonicityNot monotonic
2025-07-15T01:03:55.146206image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
14 25
 
0.8%
4 22
 
0.7%
70 21
 
0.7%
7 20
 
0.7%
35 19
 
0.6%
49 18
 
0.6%
21 17
 
0.6%
46 17
 
0.6%
11 17
 
0.6%
42 16
 
0.5%
Other values (1248) 2776
93.5%
ValueCountFrequency (%)
1 16
0.5%
1.5 1
 
< 0.1%
2 13
0.4%
2.5 1
 
< 0.1%
2.601398601 1
 
< 0.1%
3 15
0.5%
3.321428571 1
 
< 0.1%
3.330357143 1
 
< 0.1%
3.5 2
 
0.1%
4 22
0.7%
ValueCountFrequency (%)
366 1
 
< 0.1%
365 1
 
< 0.1%
363 1
 
< 0.1%
362 1
 
< 0.1%
357 2
0.1%
356 1
 
< 0.1%
355 2
0.1%
352 1
 
< 0.1%
351 2
0.1%
350 3
0.1%

frequency
Real number (ℝ)

High correlation  Skewed 

Distinct1225
Distinct (%)41.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.11383237
Minimum0.0054495913
Maximum17
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size46.4 KiB
2025-07-15T01:03:55.242978image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Quantile statistics

Minimum0.0054495913
5-th percentile0.0088935048
Q10.016339869
median0.025898352
Q30.049478583
95-th percentile1
Maximum17
Range16.99455
Interquartile range (IQR)0.033138713

Descriptive statistics

Standard deviation0.40822056
Coefficient of variation (CV)3.5861552
Kurtosis989.06632
Mean0.11383237
Median Absolute Deviation (MAD)0.012196886
Skewness24.876871
Sum337.85449
Variance0.16664402
MonotonicityNot monotonic
2025-07-15T01:03:55.345010image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 198
 
6.7%
0.0625 18
 
0.6%
0.02777777778 17
 
0.6%
0.02380952381 16
 
0.5%
0.08333333333 15
 
0.5%
0.09090909091 15
 
0.5%
0.02941176471 14
 
0.5%
0.03448275862 14
 
0.5%
0.02564102564 13
 
0.4%
0.01923076923 13
 
0.4%
Other values (1215) 2635
88.8%
ValueCountFrequency (%)
0.005449591281 1
 
< 0.1%
0.005464480874 1
 
< 0.1%
0.005479452055 1
 
< 0.1%
0.005494505495 1
 
< 0.1%
0.005586592179 2
0.1%
0.005602240896 1
 
< 0.1%
0.005617977528 2
0.1%
0.00566572238 1
 
< 0.1%
0.005681818182 2
0.1%
0.005698005698 3
0.1%
ValueCountFrequency (%)
17 1
 
< 0.1%
3 1
 
< 0.1%
2 6
 
0.2%
1.142857143 1
 
< 0.1%
1 198
6.7%
0.75 1
 
< 0.1%
0.6666666667 3
 
0.1%
0.550802139 1
 
< 0.1%
0.5335120643 1
 
< 0.1%
0.5 3
 
0.1%

qtde_returns
Real number (ℝ)

Skewed  Zeros 

Distinct213
Distinct (%)7.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean34.888477
Minimum0
Maximum9014
Zeros1481
Zeros (%)49.9%
Negative0
Negative (%)0.0%
Memory size46.4 KiB
2025-07-15T01:03:55.447630image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q39
95-th percentile100
Maximum9014
Range9014
Interquartile range (IQR)9

Descriptive statistics

Standard deviation282.86478
Coefficient of variation (CV)8.107685
Kurtosis596.20199
Mean34.888477
Median Absolute Deviation (MAD)1
Skewness21.975403
Sum103549
Variance80012.486
MonotonicityNot monotonic
2025-07-15T01:03:55.561033image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 1481
49.9%
1 164
 
5.5%
2 148
 
5.0%
3 105
 
3.5%
4 89
 
3.0%
6 78
 
2.6%
5 61
 
2.1%
12 51
 
1.7%
7 43
 
1.4%
8 43
 
1.4%
Other values (203) 705
23.8%
ValueCountFrequency (%)
0 1481
49.9%
1 164
 
5.5%
2 148
 
5.0%
3 105
 
3.5%
4 89
 
3.0%
5 61
 
2.1%
6 78
 
2.6%
7 43
 
1.4%
8 43
 
1.4%
9 41
 
1.4%
ValueCountFrequency (%)
9014 1
< 0.1%
8004 1
< 0.1%
4427 1
< 0.1%
3768 1
< 0.1%
3332 1
< 0.1%
2878 1
< 0.1%
2022 1
< 0.1%
2012 1
< 0.1%
1776 1
< 0.1%
1594 1
< 0.1%

avg_basket_size
Real number (ℝ)

High correlation 

Distinct1978
Distinct (%)66.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean236.25289
Minimum1
Maximum6009.3333
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size46.4 KiB
2025-07-15T01:03:55.660555image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile44
Q1103.2375
median172.29167
Q3281.54808
95-th percentile599.58
Maximum6009.3333
Range6008.3333
Interquartile range (IQR)178.31058

Descriptive statistics

Standard deviation283.8932
Coefficient of variation (CV)1.2016496
Kurtosis102.78169
Mean236.25289
Median Absolute Deviation (MAD)83.041667
Skewness7.7018777
Sum701198.57
Variance80595.347
MonotonicityNot monotonic
2025-07-15T01:03:55.763139image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
100 11
 
0.4%
114 10
 
0.3%
86 9
 
0.3%
73 9
 
0.3%
82 9
 
0.3%
60 8
 
0.3%
136 8
 
0.3%
75 8
 
0.3%
88 8
 
0.3%
71 7
 
0.2%
Other values (1968) 2881
97.1%
ValueCountFrequency (%)
1 2
0.1%
2 1
< 0.1%
3.333333333 1
< 0.1%
5.333333333 1
< 0.1%
5.666666667 1
< 0.1%
6.142857143 1
< 0.1%
7.5 1
< 0.1%
9 1
< 0.1%
9.5 1
< 0.1%
11 1
< 0.1%
ValueCountFrequency (%)
6009.333333 1
< 0.1%
4282 1
< 0.1%
3906 1
< 0.1%
3868.65 1
< 0.1%
2880 1
< 0.1%
2801 1
< 0.1%
2733.944444 1
< 0.1%
2518.769231 1
< 0.1%
2160.333333 1
< 0.1%
2082.225806 1
< 0.1%

avg_unique_basket_size
Real number (ℝ)

High correlation 

Distinct906
Distinct (%)30.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean17.489977
Minimum0.2
Maximum259
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size46.4 KiB
2025-07-15T01:03:55.864802image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Quantile statistics

Minimum0.2
5-th percentile2
Q17.6666667
median13.6
Q322.144643
95-th percentile46
Maximum259
Range258.8
Interquartile range (IQR)14.477976

Descriptive statistics

Standard deviation15.460127
Coefficient of variation (CV)0.88394209
Kurtosis29.324685
Mean17.489977
Median Absolute Deviation (MAD)6.6
Skewness3.4364678
Sum51910.252
Variance239.01552
MonotonicityNot monotonic
2025-07-15T01:03:55.964847image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
13 42
 
1.4%
9 41
 
1.4%
8 39
 
1.3%
16 39
 
1.3%
14 38
 
1.3%
17 38
 
1.3%
7 36
 
1.2%
11 36
 
1.2%
5 36
 
1.2%
15 35
 
1.2%
Other values (896) 2588
87.2%
ValueCountFrequency (%)
0.2 1
 
< 0.1%
0.25 3
 
0.1%
0.3333333333 6
0.2%
0.4 1
 
< 0.1%
0.4090909091 1
 
< 0.1%
0.5 12
0.4%
0.5454545455 1
 
< 0.1%
0.5555555556 1
 
< 0.1%
0.5714285714 1
 
< 0.1%
0.6176470588 1
 
< 0.1%
ValueCountFrequency (%)
259 1
< 0.1%
177 1
< 0.1%
148 1
< 0.1%
127 1
< 0.1%
105 1
< 0.1%
104 1
< 0.1%
101 1
< 0.1%
98 1
< 0.1%
95.5 1
< 0.1%
94.33333333 1
< 0.1%

Interactions

2025-07-15T01:03:52.070067image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-07-15T01:03:39.712481image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-07-15T01:03:40.687440image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-07-15T01:03:42.344831image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-07-15T01:03:43.337205image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-07-15T01:03:44.375035image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-07-15T01:03:45.316454image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-07-15T01:03:46.279857image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-07-15T01:03:47.149794image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-07-15T01:03:48.448905image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-07-15T01:03:50.205989image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-07-15T01:03:51.161098image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-07-15T01:03:52.144577image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-07-15T01:03:39.791818image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-07-15T01:03:40.764711image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-07-15T01:03:42.426964image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-07-15T01:03:43.405691image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-07-15T01:03:44.451415image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-07-15T01:03:45.393744image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-07-15T01:03:46.353661image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-07-15T01:03:47.446338image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-07-15T01:03:48.534933image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-07-15T01:03:50.282108image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-07-15T01:03:51.239400image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-07-15T01:03:52.484885image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-07-15T01:03:39.869410image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-07-15T01:03:41.447860image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-07-15T01:03:42.514562image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-07-15T01:03:43.478215image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-07-15T01:03:44.529401image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-07-15T01:03:45.471071image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-07-15T01:03:46.420829image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-07-15T01:03:47.526008image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-07-15T01:03:48.642521image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-07-15T01:03:50.363227image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-07-15T01:03:51.312430image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-07-15T01:03:52.562135image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-07-15T01:03:39.974848image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-07-15T01:03:41.527811image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-07-15T01:03:42.604250image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-07-15T01:03:43.550444image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-07-15T01:03:44.613686image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-07-15T01:03:45.551504image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-07-15T01:03:46.489416image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-07-15T01:03:47.608037image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-07-15T01:03:48.836485image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-07-15T01:03:50.447865image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-07-15T01:03:51.391140image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-07-15T01:03:52.632267image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-07-15T01:03:40.060933image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-07-15T01:03:41.602769image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-07-15T01:03:42.671351image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-07-15T01:03:43.616936image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-07-15T01:03:44.686375image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-07-15T01:03:45.621816image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-07-15T01:03:46.558052image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-07-15T01:03:47.697299image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-07-15T01:03:49.056594image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-07-15T01:03:50.524287image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-07-15T01:03:51.462288image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-07-15T01:03:52.715500image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-07-15T01:03:40.155356image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-07-15T01:03:41.764240image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-07-15T01:03:42.754591image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-07-15T01:03:43.693963image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-07-15T01:03:44.769995image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-07-15T01:03:45.705590image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-07-15T01:03:46.636708image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-07-15T01:03:47.788713image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-07-15T01:03:49.300625image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-07-15T01:03:50.650897image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-07-15T01:03:51.545288image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-07-15T01:03:52.797642image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-07-15T01:03:40.260231image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-07-15T01:03:41.849974image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-07-15T01:03:42.846325image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-07-15T01:03:43.768628image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-07-15T01:03:44.850348image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-07-15T01:03:45.789650image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-07-15T01:03:46.709991image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-07-15T01:03:47.877108image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-07-15T01:03:49.469735image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-07-15T01:03:50.724592image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-07-15T01:03:51.625302image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-07-15T01:03:52.868237image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-07-15T01:03:40.329321image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-07-15T01:03:41.919628image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-07-15T01:03:42.917132image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-07-15T01:03:43.835000image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-07-15T01:03:44.920772image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-07-15T01:03:45.866510image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-07-15T01:03:46.778789image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-07-15T01:03:47.953504image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-07-15T01:03:49.583711image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-07-15T01:03:50.794177image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-07-15T01:03:51.692195image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-07-15T01:03:52.946353image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-07-15T01:03:40.404236image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-07-15T01:03:42.010726image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-07-15T01:03:43.014167image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-07-15T01:03:43.907746image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-07-15T01:03:45.005808image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-07-15T01:03:45.947502image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-07-15T01:03:46.859157image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-07-15T01:03:48.044880image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-07-15T01:03:49.705741image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-07-15T01:03:50.872706image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-07-15T01:03:51.771873image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-07-15T01:03:53.029748image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-07-15T01:03:40.478598image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-07-15T01:03:42.089561image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-07-15T01:03:43.097818image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-07-15T01:03:43.983327image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-07-15T01:03:45.087574image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-07-15T01:03:46.038035image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-07-15T01:03:46.936977image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-07-15T01:03:48.149779image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-07-15T01:03:49.805595image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-07-15T01:03:50.946622image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-07-15T01:03:51.850586image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-07-15T01:03:53.101341image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-07-15T01:03:40.546579image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-07-15T01:03:42.163986image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-07-15T01:03:43.178630image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-07-15T01:03:44.231174image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-07-15T01:03:45.163989image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-07-15T01:03:46.118041image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-07-15T01:03:47.004495image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-07-15T01:03:48.244344image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-07-15T01:03:49.967421image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-07-15T01:03:51.011648image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-07-15T01:03:51.918720image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-07-15T01:03:53.182946image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-07-15T01:03:40.617295image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-07-15T01:03:42.256508image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-07-15T01:03:43.258985image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-07-15T01:03:44.305013image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-07-15T01:03:45.241489image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-07-15T01:03:46.205525image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-07-15T01:03:47.080447image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-07-15T01:03:48.349192image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-07-15T01:03:50.092669image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-07-15T01:03:51.091045image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
2025-07-15T01:03:51.995520image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Correlations

2025-07-15T01:03:56.044418image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
avg_basket_sizeavg_recency_daysavg_ticketavg_unique_basket_sizecustomer_idfrequencygross_revenueqtde_invoicesqtde_itemsqtde_productsqtde_returnsrecency_days
avg_basket_size1.000-0.0780.1870.404-0.1230.0280.5740.1010.7290.3840.209-0.097
avg_recency_days-0.0781.000-0.1230.1310.019-0.881-0.249-0.258-0.228-0.165-0.3980.109
avg_ticket0.187-0.1231.000-0.618-0.1310.0910.2450.0600.166-0.3770.1890.049
avg_unique_basket_size0.4040.131-0.6181.000-0.016-0.1220.106-0.1810.1480.515-0.0530.014
customer_id-0.1230.019-0.131-0.0161.000-0.002-0.0770.026-0.0710.013-0.0640.001
frequency0.028-0.8810.091-0.122-0.0021.0000.0910.0780.0810.0350.2350.017
gross_revenue0.574-0.2490.2450.106-0.0770.0911.0000.7720.9250.7460.371-0.414
qtde_invoices0.101-0.2580.060-0.1810.0260.0780.7721.0000.7180.6900.295-0.503
qtde_items0.729-0.2280.1660.148-0.0710.0810.9250.7181.0000.7320.343-0.407
qtde_products0.384-0.165-0.3770.5150.0130.0350.7460.6900.7321.0000.244-0.436
qtde_returns0.209-0.3980.189-0.053-0.0640.2350.3710.2950.3430.2441.000-0.119
recency_days-0.0970.1090.0490.0140.0010.017-0.414-0.503-0.407-0.436-0.1191.000

Missing values

2025-07-15T01:03:53.287967image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
A simple visualization of nullity by column.
2025-07-15T01:03:53.429563image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

customer_idgross_revenuerecency_daysqtde_invoicesqtde_itemsqtde_productsavg_ticketavg_recency_daysfrequencyqtde_returnsavg_basket_sizeavg_unique_basket_size
0178505391.21372.034.01733.0297.018.15222235.50000017.00000040.050.9705880.617647
1130473232.5956.09.01390.0171.018.90403527.2500000.02830235.0154.44444411.666667
2125836705.382.015.05028.0232.028.90250023.1875000.04032350.0335.2000007.600000
313748948.2595.05.0439.028.033.86607192.6666670.0179210.087.8000004.800000
415100876.00333.03.080.03.0292.0000008.6000000.07317122.026.6666670.333333
5152914623.3025.014.02102.0102.045.32647123.2000000.04011529.0150.1428574.357143
6146885630.877.021.03621.0327.017.21978618.3000000.057221399.0172.4285717.047619
7178095411.9116.012.02057.061.088.71983635.7000000.03352041.0171.4166673.833333
81531160767.900.091.038194.02379.025.5434644.1444440.243316474.0419.7142866.230769
9160982005.6387.07.0613.067.029.93477647.6666670.0243900.087.5714294.857143
customer_idgross_revenuerecency_daysqtde_invoicesqtde_itemsqtde_productsavg_ticketavg_recency_daysfrequencyqtde_returnsavg_basket_sizeavg_unique_basket_size
4268177271060.2515.01.0645.066.016.0643946.01.0000006.0645.00000066.000000
427617232421.522.02.0203.036.011.70888912.00.1538460.0101.50000015.000000
427717468137.0010.02.0116.05.027.4000004.00.4000000.058.0000002.500000
428013596697.045.02.0406.0166.04.1990367.00.2500000.0203.00000066.500000
4285148931237.859.02.0799.073.016.9568492.00.6666670.0399.50000036.000000
428912479473.2011.01.0382.030.015.7733334.01.00000034.0382.00000030.000000
430414126706.137.03.0508.015.047.0753333.00.75000050.0169.3333334.666667
4308135211092.391.03.0733.0435.02.5112414.50.3000000.0244.333333104.000000
431315060301.848.04.0262.0120.02.5153331.02.0000000.065.50000020.000000
431812558269.967.01.0196.011.024.5418186.01.000000196.0196.00000011.000000